Novel Insights into DNA Methylation Features inSpermatozoa: Stability and PeculiaritiesCsilla Krausz1,2*., Juan Sandoval3., Sergi Sayols3, Chiara Chianese1, Claudia Giachini1, Holger Heyn3,
Manel Esteller3,4,5*
1 Department of Clinical Physiopathology, Andrology Unit, University of Florence, Florence, Italy, 2 Fundacio Puigvert, Barcelona, Catalonia, Spain, 3 Cancer Epigenetics
and Biology Program (PEBC), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Catalonia, Spain, 4 Department of Physiological Sciences II, School of Medicine,
University of Barcelona, Barcelona, Catalonia, Spain, 5 Institucio Catalana de Recerca i Estudis Avancats (ICREA), Barcelona, Catalonia, Spain
Abstract
Data about the entire sperm DNA methylome are limited to two sperm donors whereas studies dealing with a greaternumber of subjects focused only on a few genes or were based on low resolution arrays. This implies that information aboutwhat we can consider as a normal sperm DNA methylome and whether it is stable among different normozoospermicindividuals is still missing. The definition of the DNA methylation profile of normozoospermic men, the entity of inter-individual variability and the epigenetic characterization of quality-fractioned sperm subpopulations in the same subject(intra-individual variability) are relevant for a better understanding of pathological conditions. We addressed thesequestions by using the high resolution Infinium 450K methylation array and compared normal sperm DNA methylomesagainst somatic and cancer cells. Our study, based on the largest number of subjects (n = 8) ever considered for such a largenumber of CpGs (n = 487,517), provided clear evidence for i) a highly conserved DNA methylation profile amongnormozoospermic subjects; ii) a stable sperm DNA methylation pattern in different quality-fractioned sperm populations ofthe same individual. The latter finding is particularly relevant if we consider that different quality fractioned spermsubpopulations show differences in their structural features, metabolic and genomic profiles. We demonstrate, for the firsttime, that DNA methylation in normozoospermic men remains highly uniform regardless the quality of spermsubpopulations. In addition, our analysis provided both confirmatory and novel data concerning the sperm DNAmethylome, including its peculiar features in respect to somatic and cancer cells. Our description about a highly polarizedsperm DNA methylation profile, the clearly distinct genomic and functional organization of hypo- versus hypermethylatedloci as well as the association of histone-enriched hypomethylated loci with embryonic development, which we nowextended also to hypomethylated piRNAs-linked genes, provides solid basis for future basic and clinical research.
Citation: Krausz C, Sandoval J, Sayols S, Chianese C, Giachini C, et al. (2012) Novel Insights into DNA Methylation Features in Spermatozoa: Stability andPeculiarities. PLoS ONE 7(10): e44479. doi:10.1371/journal.pone.0044479
Editor: Joel R. Drevet, Clermont-Ferrand Univ., France
Received May 22, 2012; Accepted August 7, 2012; Published October 2, 2012
Copyright: � 2012 Krausz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the European Research Council (ERC) Advanced Grant EPINORC, the Ministerio de Ciencia e Innovacion (MICINN) grantSAF2011-22803, the Health Department of the Catalan Government (Generalitat de Catalunya), the Italian Ministry of University (grant PRIN 2010-2012 to CK), theSpanish Ministry of Health (grant FIS -PI11/02254). JS is a ‘‘Juan de la Cierva’’ Researcher. ME is an Institucio Catalana de Recerca i Estudis Avancats (ICREA)Research Professor. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: [email protected] (CK); [email protected] (ME)
. These authors contributed equally to this work.
Introduction
Human spermatogenesis is an outstandingly complex biological
process which requires the concerted action of several thousands of
genes [1]. An interesting feature of this biological process is the
extremely large inter-individual variability of sperm production in
healthy fertile men. The entity of this variation is well illustrated by
a large recent study, reporting that total sperm number in the so
called normal range (defined as 5th -95th percentile), varies from
40 millions to several hundred millions [2]. While a few genetic
variants have been studied in relation to spermatogenic efficiency
in normozoospermic men [3–6], the epigenetic aspects of such
variations in the normozoospermic range is completely unex-
plored.
Apart from the large inter-individual variability of the above
mentioned quantitative traits of spermatogenesis, semen of
normozoospermic men contains a qualitatively (in terms of
motility and morphology) heterogeneous sperm population. With
the advent and diffusion of assisted reproductive techniques, a
number of sperm selection methods have been developed in order
to obtain sperm subpopulations enriched with highly motile and
morphologically normal spermatozoa to be used for in vivo or in
vitro insemination. The rationale behind selection is mainly related
to a predicted higher functional competency and a higher genomic
integrity of selected spermatozoa. Interestingly enough, despite the
same testicular environment, biochemical markers [7,8] as well as
DNA integrity [9–12] show differences in distinct sperm fractions
belonging to the same individual. It is still unknown whether these
fractions also show differences in their methylation level.
Given that epigenetic signals such as DNA methylation and
histone modifications are crucial for the proper functioning of the
genome, phenotypic differences in sperm production (quantitative
as well as qualitative traits) at both inter- and intra-individual level
may also be due to an epigenetic variation. This hypothesis seems
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to be plausible if we consider that the epigenome of mature
spermatozoa mirrors a series of sequential epigenetic reprogram-
ming events (demethylation and de novo methylation) which may
generate substantial epigenetic variability. The sole study address-
ing the question about intra- and inter-individual DNA methyl-
ation changes in normozoospermic men was based on a 12,198-
feature CpG island microarray [13]. The authors reported
significant variations for 6 genes both at the intra- and inter-
individual level, concluding that epigenetic variations may
contribute to the variable semen phenotype. On the other hand,
a limited inter-individual variability in DNA methylation was
observed in two recent studies comparing two sperm donors by
using a methylated DNA immunoprecipitation (MeDIP) proce-
dure and promoter arrays [14] and a genome-wide shotgun
bisulfite sequencing [15].
With respect to intra-individual variability of epigenetic marks
in quality-fractioned sperm populations from normozoospermic
and oligozoospermic men, data are available only for promoter
CpG islands of two spermatogenesis candidate genes, DAZ and
DAZL [16]. In this study, significant differences in the DAZL
promoter methylation were observed between normal and
defective germ cell fractions from the same individual. Other
evidences for a potential association of DNA methylation defects
and impaired sperm quality derives from studies based on the
comparison of men with different sperm parameters including
subjects with abnormally low sperm motility/morphology and
sperm number [16–25].
Given the paucity of data on intra- and inter-individual
variability of sperm DNA methylation, we aimed to provide a
detailed description based on the analysis of a total of 487,317
CpG sites. Our first question was whether different quality-
fractioned sperm populations deriving from the same individual
displayed differences at the DNA methylation level i.e whether
‘‘good’’ and ‘‘poor’’ quality spermatozoa differ not only in their
metabolic markers and genome integrity but also in their
methylation status. Our second aim was to assess the level of
inter-individual variability by comparing the genome-wide meth-
ylation profiles of whole sperm populations and quality-fractioned
sperm subpopulations of different normozoospermic subjects.
Finally, we aimed to get further insights into the sperm DNA
methylome through the investigation on loci with ‘‘variable’’ and
‘‘conserved’’ DNA methylation levels between individuals and
their relationship with chromatin modifications. In addition, in
this part of the study, we focused on a singular topic, not addressed
by others until now, that concerns the sperm methylation status of
piRNAs (PIWI-interacting RNAs). This peculiar class of small non
coding RNAs are specifically expressed in the testis and seem to be
involved in the maintenance of genomic stability and germ cell
function through the silencing, via DNA methylation, of mobile
genetic elements such as transposons (reviewed in Aravin et al.
[26]). In fact, knock-out mice models for the proteins involved in
the piRNA biogenesis (MIWI, MILI, MIWI2) revealed a
restoration of transposon activity, which is thought to be the
cause of the observed sterility due to meiotic arrest [27,28].
However, given that piRNAs have recently been identified also in
human cancer cells and somatic cells, it has been proposed that
piRNAs regulate gene expression more broadly than previously
predicted (for review see Juliano et al. [29] and Siddiqi and
Matushansky [29,30]. In order to provide new insights into this
largely unexplored topic, we investigated the piRNAs methylation
status in spermatozoa and performed a comparative analysis with
a differentiated somatic cell type (B cell) and a colorectal cancer
cell line (HCT-116).
Our study, based on the largest genome-wide DNA methylation
analysis available to date in a group of normozoospermic men,
allowed us to both define the ‘‘normal’’ sperm DNA methylome
with its peculiar features and discover a potential new role for
sperm piRNAs in embryonic development.
Materials and Methods
SubjectsEthics statement: All participating subject signed an informed
consent and the project has been approved by the local Ethical
Committee of the University Hospital Careggi.
Eight healthy normozoospermic individuals of Italian origin
belonging to the upper normal range of sperm number were
analyzed in this study. Sperm parameters, age and relevant
phenotypic information are reported in Table S1. Considerable
care was taken for the selection of subjects in order to provide a
homogeneous group in terms of life style factors, age, BMI and
semen characteristics. Special attention was paid in selecting only
semen samples devoid of contaminating somatic cells in their
ejaculate. The absence of leucocytes or uroepithelial cells was
assessed by scoring 5 stained slides at the light microscope in all 8
samples. The purity of the swim-down fraction deriving from
contaminating cells was documented by checking additional 5
slides at light microscopy. This procedure based on a two-step
purity check granted a biologically irrelevant, if any, contamina-
tion in both whole semen and the swim-down fractions.
Three aliquots were obtained from each individual correspond-
ing to: 1) whole sperm population after 1 hour from semen
collection; 2) swim-up fraction; 3) swim-down fraction. For sample
EC7, the swim-down fraction has been excluded due to DNA
degradation. For 3 samples whole, semen at 2 Sperm DNA
methylation profile largely hours (corresponding to the time at
which the swim-up procedure ends) were also available for the
comparison with the other fractions.
Sperm selectionWhole semen has been centrifuged on a 25% Percoll gradient
(20 minutes) before the standard swim-up separation technique.
Although much care was taken for the selection of samples in
terms of lack of contaminating cells, this preliminary step further
ensured the purity of the sperm population. The swim-up
procedure allows spermatozoa with progressive motility to ‘‘swim
up’’ into the culture medium while hypomotile/immotile sperma-
tozoa remain behind. The upper fraction is denominated ‘‘Up’’,
whereas the fraction containing hypo/immotile spermatozoa is
indicated in this manuscript as ‘‘Down or Dn’’.
Sperm DNA extractionSperm DNA was extracted with an user-developed version of
the QIAampH DNeasy&Tissue Kit purification protocol. Fresh
washed (in PBS) sperm was incubated 1:1 with a lysis buffer
containing 20 mM TrisCl (pH 8), 20mM EDTA, 200 mM NaCl
and 4% SDS, supplemented prior to use with 100 mM DTT and
250 ug/ml Proteinase K. Incubation was performed for 4 hours at
55uC with frequent vortexing. Prior to processing in the columns,
200 ul of absolute ethanol and 200 ul of the kit-provided lysis
buffer were added to the samples. Then, purification was
performed according to kit instructions.
Microarray-based DNA methylation analysisDNA was quantified by Quant-iTTM PicoGreen dsDNA
Reagent (Invitrogen) and the integrity was analyzed in a 1.3%
agarose gel. Bisulfite conversion of 600 ng of each sample was
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performed according to the manufacturer’s recommendation for
Illumina Infinium Assay. Effective bisulphite conversion was
checked for three controls that were converted simultaneously
with the samples. 4 ml of bisulfite converted DNA were used to
hybridize on Infinium HumanMethylation 450 BeadChip, follow-
ing Illumina Infinium HD Methylation protocol. Chip analysis
was performed using Illumina HiScan SQ fluorescent scanner.
The intensities of the images are extracted using GenomeStudio
(2010.3) Methylation module (1.8.5) software. Methylation score of
each CpG is represented as beta (b) value (b value ,0.2 is
considered as hypomethylated, .0.8 as hypermethylated). The
450K DNA Methylation array includes 485,764 cytosine positions
of the human genome. From these cytosine sites, 482,421 positions
(99.3%) are CpG dinucleotides, whilst only 3,343 sites (0.7%)
correspond to CNG targets. Thus, from this point on we will use
the term CpG, except when we refer specifically to putative CNG
methylation. A general depiction of the 450K platform design,
regarding functional genome distribution, CpG content and
chromosome location, is reported in a previous validation study
from our laboratory [31].
Data filteringThe 450K DNA methylation array by Illumina is an
established, highly reproducible method for DNA methylation
detection and has been validated in two independent laboratories
[31,32].
Every beta value in the 450 K platform is accompanied by a
detection p-value. We based filtering criteria on the basis of these
p-values reported by the assay. We examined two aspects of
filtering out probes and samples based on the detection p-values,
selecting i) a threshold and ii) a cut-off. Previous analyses indicated
that a threshold value of 0.01 allows a clear distinction to be made
between reliable and unreliable beta values [31]. We selected the
cut-off value as 10%. Following this criterion, we excluded all
probes with detection p-values .0.01 in 10% or more of the
samples and a total of 485,317 probes were included in the final
analysis. We expect similar methylation level in neighbouring CpG
sites given the strong correlation between CpG site methylation
levels up to 150 bp.
Statistical analysisIn order to identify differentially methylated CpG sites between
different quality fractioned sperm populations, a non parametric
test (Wilcoxon rank sum test) has been performed. Linear
regression coefficient has been calculated (Spearman’s rho) both
for intra and inter-individual variability of methylation levels. For
all comparisons of methylation levels between different subgroups
Fischer exact test was performed.
For the estimation of the degree of epigenetic dissimilarity
between individuals we measured the Euclidean distances between
two samples using the following equation:
d a,bð Þ~HSin~1 ai{bið Þ2
Where ai and bi represent the beta value for the i-essim CpG of
samples ‘‘a’’ and ‘‘b’’, and ‘‘n’’ the number of CpG sites selected.
In addition, to estimate the inter-individual variability of the
methylation status in the promoters of the 6 genes previously
described as highly variable, we calculated for each gene a 100,000
permutations test with the distances of the three groups, in order to
obtain a random distribution of possible mean distances and get a
p-value for the mean variability among individuals in a group (the
area below the distribution curve).
For the estimation of enrichment in biological processes we
performed a hypergeometric test on biological processes defined
by Gene Ontology [33].
Results
Comparison of genome-wide DNA methylation level indifferent quality-fractioned sperm populations derivingfrom eight normozoospermic men
The ejaculate of a normozoospermic man contains a qualita-
tively heterogeneous sperm population (in terms of different
motility, morphology, metabolic and genomic features). This part
of the analysis focused on intra-individual variation and addressed
the biological question whether there are significant differences in
methylation profiling between the ‘‘up’’ (enriched with highly
motile and morphologically normal spermatozoa) versus ‘‘down’’
(poorly motile/immotile and morphologically abnormal sperma-
tozoa) semen fractions in each subject.
Analysis of intra-individual variation in 485,317 CpG
loci. By performing linear regression analysis, we observed an
extremely high correlation (Pearson correlation coefficient ranging
from R2 = 0.9896 to R2 = 0.9982) between ‘‘good’’ and ‘‘poor’’
quality sperm suspensions in all subjects (Table S2A). A represen-
tative example is given for sample EC01 in Figure 1. Accordingly,
unsupervised hierarchical cluster analysis of the two tested groups
was unable to cluster the ‘‘up’’ and ‘‘down’’ fractions into two
distinct groups. Similarly, no significant differences were observed
following comparison of the methylation levels in the 485,317
CpG sites between different sperm fractions (‘‘up’’ versus ‘‘down’’,
whole sperm population versus ‘‘down’’, whole sperm population
versus ‘‘up’’). By comparing epigenetic distances between the ‘‘up’’
and ‘‘down’’ fractions of the same individual, we found no
significant differences except for one sample (EC12) with
p = 0.018. Interestingly, this sample showed the lowest sperm
count among the 8 normozoospermic individuals. Separately, we
analyzed the intra-individual variation in selected CpG loci
previously reported to be associated with poor sperm quality. To
begin with, a few imprinted loci were analyzed in previous studies
in relationship with a wide range of infertile phenotypes
(oligozoospermia, oligoasthenozoospermia, asthenozoospermia).
All previous studies reported methylation changes in a portion of
infertile men, suggesting that impaired sperm production may be
associated with methylation defects. A total of 2,386 CpGs
belonging to 45 imprinted genes are present on the 450K array
(24) and we analyzed the methylation status of their promoter
regions in the ‘‘up’’ and ‘‘down’’ fractions. Similarly, we
investigated on 289 CpGs belonging to 10 genes (DAZ, DAZL,
DAZAP, HRAS, KDM3A, MTHFR, NTF3, PAX8, RASGRF1, SFN)
showing DNA methylation changes in infertile men compared to
normozoospermic controls as well as in different quality-fractioned
sperm populations (such as DAZ and DAZL). In all cases, a
homogeneous methylation pattern was observed in the two
fractions derived from the same individual and, accordingly, the
two sperm fractions derived from all analyzed subjects did not
cluster separately (Figure 2 and 3).
Assessment of inter-individual variability in genome-
wide DNA methylation profile. Although all subjects be-
longed to the upper normal range of sperm number, the whole
semen fraction of each individual included a different proportion
of ‘‘good’’ and ‘‘poor’’ quality spermatozoa. The most homoge-
neous sperm population containing the best quality spermatozoa
was the ‘‘up’’ fraction. A slightly more pronounced inter-individual
variability in DNA methylation profile has been observed
compared to intra-individual variability between sperm fractions.
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However, the linear regression coefficients were always .0.98
(Table S2B). A representative scatter plot comparing two individ-
uals is shown in Figure 4 A–C.
In order to further explore inter-individual variability, we
analyzed each type of sperm fraction using two additional
approaches: i) we quantified the number of CpGs showing a
standard deviation .0.2 in the methylation level (beta value)
between individuals; ii) we measured the epigenetic distance (by
the use of the Euclidean distance formula reported in materials
and methods) between the methylation level of CpGs in different
subjects. The number of differentially methylated loci i.e. showing
a SD .0.2 between different subjects was 1,591 in the whole
semen, 1,207 in the ‘‘down’’ fraction and 1,675 in the ‘‘up’’
fraction. This implies that for all comparisons the number of CpGs
above the established threshold level was very low, representing
,0.3% of all loci tested. The GO analysis of genes related to the
1,675 differentially methylated sites did not show any germ cell
specific function. (data not shown).
By performing the comparison of DNA methylation distances
across individuals considering all 485,317 CpG sites, a significantly
higher variability has been observed in the swim-down sperm
fraction (p = 0.021) in respect to the swim-up fraction (Figure 4D).
However, it is worth noticing that the coefficient of variation is still
very low in the swim-down fraction, e.g. 14% which indicates that
the maximum epigenetic distance between individuals was limited
to 45, that is significantly lower than the maximum distance
possible e.g. 696.(see Table S3).
Assessment of methylation level in six gene promoters
previously reported as having the highest intra and inter-
individual variation. Significant DNA methylation variations
have been reported for promoters of the following 6 genes: BRCA1,
BRCA2, HTT (HD), DMPK (DM1), PSEN1, PSEN2 by Flanagan
et al. [13]. In order to evaluate the entity of inter-individual
variability, we calculated Euclidean distances for the beta values of
the CpG sites in the above gene promoters among individuals of
the three groups (Whole semen, ‘‘Down’’ and ‘‘Up’’), plots are
shown in Figure 5A–C. In addition, by performing permutation
test of the epigenetic distances we found significant inter-individual
differences for 4 out of 6 genes (HTT,DMPK, PSEN1, PSEN2) in
the swim-down sperm fraction (p values:2E-05; 0.00096; 0.00348;
0.02, respectively), while we observed no relevant variation in the
swim-up fraction. In the whole sperm population sample,
significance was reached only for BRCA1 (0.01136).
Sperm genome-wide methylome description and itscomparison with differentiated somatic cells
Sperm DNA methylation profile: general features. Given
that the swim-up fraction, being enriched in the best quality
spermatozoa, is the one used for assisted reproductive techniques,
we aimed to provide a detailed description of genome wide DNA
methylation profile of these cells. The average DNA methylation
level of the 485,317 CpG sites was 45% (median value 35%).
However, an interesting feature of the sperm DNA methylome is
the polarization of DNA methylation level towards the two
extremes: 86% of all markers are either severely hypomethylated
(,20%) or strongly hypermethylated (.80%). Intermediate
methylation level (20–80%) was observed only for 14% of CpGs.
We defined, in each subject, the number of hypomethylated and
hypermethylated loci for the whole genome as well as for the sex
chromosomes and autosomes, separately (Table 1). The coefficient
of variation of DNA methylation levels was minimal between
subjects for the hypomethylated loci (0.9%) and slightly higher for
Figure 1. Scatter plots reporting CpGs methylation levels between different samples deriving from the swim-up sperm selectionprocedure in the same individual EC01: (A) swim-up (Up) sperm fraction versus swim-down (Dn) sperm fraction; (B) whole spermpopulation at1h (Ws 1 h) versus whole sperm population at 2 h (Ws 2h); (C) whole sperm population at 1h versus swim-downsperm fraction; (D) whole sperm population at1h versus swim-up sperm fraction. R2 = Pearson coefficient.doi:10.1371/journal.pone.0044479.g001
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hypermethylated loci (2.8%), suggesting a highly conserved profile
both for hypo and hypermethylated loci. Accordingly, we found
95.8% of all hypomethylated loci to be conserved between
individuals (n = 220,300 CpGs), whereas in the hypermethylated
loci the concordance was slightly lower, 86.1% (n = 161,542
CpGs).
The separate analysis of autosomal (a total of 473,681 CpGs),
X-linked (a total of 11,220 CpGs) and Y-linked CpGs (a total of
416 CpGs) revealed that X-linked loci are significantly more
frequently hypomethylated than autosomal loci (64.5% versus
45.8%; p,2.2 xE-16), as was the case also for the Y–linked loci
(65.2% versus 45.8%, p = 3.458xE-5) (Table 1). On the other
hand, autosomal loci were significantly more frequently hyper-
methylated than X-linked loci (38.1% versus 21.6%; p,2.2xE-16).
It is also worth noticing, that the highest percentage of
‘‘conserved’’ hypomethylated loci was found for the X-linked loci
(96.1%).
Sperm DNA methylation profile: comparative analysis of
regions with conserved hypo/hyper methylation and
differentially methylated loci between
individuals. Subsequently, we identified loci displaying the
same DNA methylation pattern in all subjects (‘‘conserved’’ hypo
or hyper) as well as loci showing different DNA methylation
patterns (‘‘variable’’ or ‘‘differentially methylated’’ loci). We
analyzed the functional genomic distribution (promoter, body,
39UTR, and intergenic), CpG content and neighborhood context.
For the latter, we referred to: i) ‘‘island’’ as a DNA sequence
(.200-bp window) with a GC content greater than 50% and an
observed: expected CpG ratio of more than 0.6.; ii) ‘‘shore’’ as a
sequence 0–2 Kb distant from the CpG island; iii) ‘‘shelf’’ as a
sequence 2–4 Kb distant from the CpG island; iv) ‘‘open sea/
Figure 2. Heatmap displaying the methylation status of CpG loci (n = 2386) mapping in the promoters of 45 imprinted genes inrelation to quality-fractioned sperm populations (i.e. swim-up ‘‘up’’ and swim- ‘‘dn’’ sperm fractions). A) The dendrograms above theheatmap show hierarchical clustering based on the methylation data alone. Sperm populations and CpG loci are represented by columns and rows,respectively. Each cell indicates the CpG methylation level for one site in each sample. Methylation levels are represented in the scale on the right sideof the heatmap and are referred lowest to highest as green (0.0) to red (1.0). (B) List of the 45 imprinted gene available in the array.doi:10.1371/journal.pone.0044479.g002
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others’’ as the remaining sequence. The methylation categories
were also analyzed in relationship with genomic locations related
to RNA transcription (coding, non-coding and intergenic). Sharp
differences were observed between the ‘‘conserved’’ hypo and
hyper-methylated loci according to the functional genomic
distribution as well as for the CpG and neighborhood context
(Figure 6). Among all ‘‘conserved’’ hypomethylated loci 63.6%
belonged to promoters, whereas this percentage was significantly
lower in the hypermethylated loci, 19.5% (p = 4,14E-05). A
significant difference was observed also in the methylation status
of gene body-linked CpGs which made up 47.7% of ‘‘conserved’’
hypermethylated loci and only a minority of the ‘‘conserved’’
hypomethylated loci (17.3%; p = 0.001357). Given the high
prevalence of promoters in the hypomethylated sites, almost
90% of the hypomethylated CpGs correspond to islands and
shores (58.7% and 29.9%, respectively). On the contrary, 80% of
‘‘conserved’’ hypermethylated sites are either in the CpG poor
island shelves or in ‘‘open sea’’ regions (18% and 63.3%,
respectively).
Differentially methylated loci (defined as .0.2 standard
deviation between individuals) have been identified only for
0.3% of all analyzed CpGs. Interestingly, the percentage of
‘‘variable’’ regions were lower in X-linked loci (0.2%) and were
completely absent in the 416 Y-linked loci. Intriguingly, the
pattern of ‘‘variable’’ CpGs was more similar to the ‘‘conserved’’
hypermethylated loci than to the ‘‘conserved’’ hypomethylated
ones, as a matter of fact the variation in DNA methylation
between individuals is more pronounced in CpG-poor regions
such as gene body, intergenic and ‘‘open sea’’ (Figure 6).
Gene Ontology analysis of ‘‘conserved’’ hypo and
hypermethylated loci. Our next question was whether hypo
and hypermethylated loci were linked to specific biological
processes. By performing GO analysis, we found that the two
methylation patterns are involved in completely distinct cellular
processes (Table S4A). An outstandingly high association has
been observed between hypomethylation and genes involved in
metabolic and biosynthetic processes (among the first 20
significant associations, 11 are linked to metabolic and 5 to
biosynthetic processes). On the contrary, hypermethylated sites,
while associated with several different biological processes, did
not show any association with metabolic and biosynthetic genes.
Analysis of DNA methylation levels in histone-enriched
loci and gene ontology analysis. In a previous study,
Hammoud et al.[14] defined the position of histone enriched loci
in the sperm genome. We crossed our list of ‘‘conserved’’ hypo and
hypermethylated loci with the list of histone positions referring to
Figure 3. Heatmap displaying the methylation status of CpG loci (n = 297) mapping in 10 selected genes in relation to quality-fractioned sperm populations (i.e. swim-up ‘‘up’’ and swim-down ‘‘dn’’ sperm fractions). A) The dendrograms above the heatmap showhierarchical clustering based on the methylation data alone. Sperm populations and CpG loci are represented by columns and rows, respectively.Each cell indicates the CpG methylation level for one site in each sample. Methylation levels are represented in the scale on the right side of theheatmap and are referred lowest to highest as green (0.0) to red (1.0). B) Scatter plot reporting CpGs methylation levels between quality-fractionedsperm populations (Up vs Dn) among different individuals. R2 = Pearson coefficient. C) List of the 10 analyzed genes, selected because previouslyreported as differently methylated in infertile men compared to normozoospermic controls.doi:10.1371/journal.pone.0044479.g003
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the top 9,841 regions (FDR 40 cut off) and found a total of 30,591
CpGs in our array. The large majority (98.9 %) of these CpGs
were hypomethylated (n = 30,244) whereas only 1.1% of all
histone-retained sites were hypermethylated (n = 347). Similarly
to the globally considered ‘‘conserved’’ hypo/hypermethylated
sites, we observed sharp differences in the distribution according to
functional genomic and CpG content criteria between hypo and
hypermethylated loci enriched in histones, since promoters and
islands are prevalent in the hypomethylated loci (74% and 90.5%,
respectively), and scarcely represented in the hypermethylated loci
(22.8% and 40.3%, respectively) (Figure 7). Hypermethylated loci
at the global level (including both histone-enriched and histone-
depleted i.e. protaminized segments) have been found mainly
outside of the islands as well as shore and shelf areas and involve
63.3% of the so called ’’open sea/others’’ genomic regions
whereas the same regions are present only in 21.6 % of
hypermethylated histone-retained CpGs. Moreover, in hyper-
methylated loci overlapping with histones, islands were represent-
ed almost seven times more than in hypermethylated regions at the
global level (40.3% versus 6.7%) (See Figure 6 and 7 ).
In agreement with Hammoud et al. [14] and Vavouri and
Lenher [34], we also found that histone-retained hypomethylated
regions were enriched with developmental genes (Table S4B)
indicating that genes mapping to histone enriched regions are
related to completely distinct biological processes compared to the
hypomethylated region at the global level (i.e. involved in
metabolism). Concerning histone enriched hypermethylated
regions the level of associations was much lower with specific
biological processes (below p,1024) and was more heterogeneous.
An additional datum supporting the link between hypomethyla-
tion and histone retention of developmental genes was that among
the 106 developmental genes available in the array, 62 presented
in their promoters CpGs with ,20% of methylation level as well
as histone retention. On the contrary, no overlap with histones was
observed in developmental gene promoters showing hypermethy-
lation.
Comparison of the sperm DNA methylome with a
differentiated somatic cell type. The average percentage of
hypomethylated loci was significantly higher in sperm cells of the 8
subjects at the global, autosomal and sex-chromosomal levels
(p,0.05 for all comparisons) compared to the differentiated
somatic cell (Figure 8). On the contrary, no differences were found
concerning the percentage of hypermethylated sites. The most
striking difference in hypomethylation concerned the X and Y
chromosomes (Figure 8 and Table 1). Next, we searched for the
number of equally methylated CpGs between spermatozoa and B
cells. We found that 4% showed a differentially methylated pattern
whereas 485,317 CpGs were equally methylated between the two
Figure 4. Representative scatter plots reporting CpG methylation levels between different individuals EC01 and EC10. (A) swim-up(Up) sperm samples; (B) swim-down (Dn) sperm samples; (C) whole sperm population at 1 h (Ws 1 h) samples; (D) Box plot representing the inter-individual variability of DNA methylation levels in total CpGs from the swim-up, swim-down and whole sperm population at1h samples. The medianvalue is shown. * corresponds to p value = 0.0213; R2 = Pearson coefficient. The boxes describe the lower quartile (Q1, 25%), median (Q2, 50%) andthe upper quartile (Q3, 75%); the whiskers extend 1.5 times the IQR from the box.doi:10.1371/journal.pone.0044479.g004
Sperm DNA Methylation Profiling
PLOS ONE | www.plosone.org 7 October 2012 | Volume 7 | Issue 10 | e44479
Sperm DNA Methylation Profiling
PLOS ONE | www.plosone.org 8 October 2012 | Volume 7 | Issue 10 | e44479
types of cells (96%). (Figure 9). Among the almost 20,000 CpGs
showing a sperm-specific differentially methylated pattern (either
hypo- or hypermethylation), those hypomethylated CpGs in
spermatozoa, which were found to be hypermethylated in B cells,
are the most represented proportion (76%). We analyzed the
functional genomic distribution, CpG content and the associated
RNA transcripts in the differentially methylated sites, separately
for hypo-and hypermethylated sperm specific CpGs. The only
significant difference consisted in the overrepresentation of ‘‘open
sea/others’’ elements in the category of CpG content/neighbor-
hood context of the sperm-specific hypermethylated CpGs
compared to the sperm-specific hypomethylated sites (71% versus
30%, p = 0.00086). The 15,799 CpGs showing a sperm-specific
hypomethylated pattern included 6,140 gene promoter CpGs
which belong to 3,344 distinct genes. The function of these genes is
mainly related to metabolic and biochemical processes, and
among the strongest associations resulted also DNA methylation
involved in gamete generation and piRNA metabolic processes
(Table S5A). Furthermore, we identified a total of 195 genes with
sperm-specific hypomethylated gene promoters which were
associated with histone-retained regions and involved in develop-
mental processes (organogenesis, especially neuronal development)
and in spermatogenesis (Table S5B).
piRNAs and DNA methylation status. We were interested
in providing a detailed description of the methylation status of
piRNA-linked CpGs in spermatozoa, B cells and cancer cells. To
accomplish this purpose, we crossed the position of 15,000
piRNAs with unique positions in the genome present in the
piRNABank (http://pirnabank.ibab.ac.in/) with the positions of
the 487,517 CpGs available in the array. In order to include
potential regulatory sequences, we extended the piRNA positions
to 62 Kb and through these criteria a total of 2,591 unique
piRNAs have been found to be covered by 7,528 CpGs on the
array. In spermatozoa, 80% of the total array-available piRNA-
linked CpGs (n = 6050) revealed either very high or very low
methylation levels. In fact, similarly to the global sperm DNA
methylome, sperm piRNA-linked CpGs showed a sharply
polarized methylation profile being 48.6% hypomethylated
(,20% methylation level) and 31.8% hypermethylated (.80%
methylation level). We found a significantly higher proportion of
piRNA-linked CpGs within the total hypomethylated loci (3,657
out of 220,300) compared to those found within the hypermethy-
lated loci (2,392 out of 161,542 ) (p = 1.585E-05). In order to
obtain more comprehensive characterization of sperm specific
piRNAs-linked CpG methylation, we performed a comparative
analysis with a differentiated somatic cell type (B cell) and a colon
cancer cell type (HCT116).
By comparing the three cell types, we observed substantial
differences in the methylation status of the piRNA-linked CpGs. In
somatic cell, 95% of piRNA-linked CpGs show an intermediate
methylation level, with a remaining 4.5% hypomethylated and
0.4% hypermethylated loci. On the contrary, similar to sperma-
tozoa, cancer cells showed a polarization toward hypo/hyper-
methylation, but with an opposite pattern of methylation
compared to spermatozoa i.e. 26% of the HCT116 cell piRNA-
linked CpGs was hypomethylated and 53% was hypermethylated.
Next, we aimed to define the number of overlapping and
distinct CpGs within the three cell types showing the same DNA
methylation pattern (hypo or hypermethylation) ( Figure 10).
Sperm DNA methylation profile largely overlaps with that of the
cancer cell, especially for the hypermethylated loci (86.8%). The
overlap was 51.5% within the hypomethylated CpGs. On the
contrary, there is only a limited number of overlapping CpGs with
the somatic cell, with the largest overlap within hypomethylated
loci (8.9 %) and the lowest for the hypermethylated CpGs (1.1%).
Given the functional importance of histone-retained regions in
spermatozoa [14; [34], we extended our analysis to histone-
retained regions associated to piRNAs A total of 408 piRNA-
linked CpGs revealed to be overlapping with histone-retained
regions in spermatozoa and interestingly, 97% of them showed
,20% of methylation level. When comparing the 342 hypo-
methylated piRNA-linked CpGs in B cells to the 3,657
hypomethylated piRNA-linked CpGs in the sperm, we found that
all, except 16 CpGs, were also present in spermatozoa. However,
when comparing the same 342 hypomethylated piRNA-linked
CpG sites in B cells to the 408 hypomethylated histone enriched
piRNA-linked CpG sites in the sperm, only 3.2% of them
overlapped. The same phenomenon was observed for the cancer
cell i.e. almost all piRNA-linked hypomethylated loci in the
HCT116 cell (1883 out of 1959) overlapped with the 3657
hypomethylated piRNA-linked CpGs in the sperm whereas only
263/1959 were shared between the two cell types when comparing
to the sperm histone–enriched loci (408 CpG sites).
We next focused on the characterization of sperm-specific
piRNAs. Accordingly, we identified the sperm-specific hypo and
hypermethylated sites i.e. not overlapping with any of the two
other cell types. We performed a GO analysis for the genes
overlapping sperm-specific piRNA in order to define the type of
biological processes in which the associated genes are involved
(Table S6). A total of 213 genes were identified in association with
piRNAs showing exclusive hypomethylation in the spermatozoa.
Strikingly, some of these genes are involved in embryonic
development.
Discussion
The mammalian germ line undergoes extensive epigenetic
reprogramming during development and gametogenesis. In pre-
implantation embryo, a pattern of somatic-like DNA hypermethyla-
tion is established in all cells, including those which are destined to
give origin to germ cells. This active de novo methylation process is
followed by a widespread erasure of DNA methylation in primordial
germ cells. Subsequently, another wave of de novo methylation takes
place during spermatogenesis, ensuring a male germ line specific
pattern of DNA methylation. The understanding of this complex
process and the description of sperm DNA methylome have multiple
implications, including evolutionary [15] and clinical aspects [35].
The entire sperm DNA methylome has been recently described by
Molaro et al. [15] and it is based on the analysis of the whole semen
(without quality fractioning) belonging to two sperm donors. Studies
dealing with a larger group of subjects analyzed only a few genes or
were based on low resolution arrays [16–19,21–25]. This implies
Figure 5. Intra-group epigenetic distances for the promoters of BRCA1, BRCA2, HTT, DMPK1, PSEN1 and PSEN2 genes. This distancerepresents the net dissimilarity of DNA methylation profiles between two sequences: the higher the distance, the more dissimilar are the comparedsamples. Different individuals were crossed with each other and Euclidean distances were calculated for beta-values of CpG sites as a marker of inter-individual variability in three different sperm subpopulations: A) Whole sperm population; B) swim-down and C) swim-up fractions. Numbers on the Xaxis indicate the identity of the pair-wise comparisons inside the experimental group: individuals EC01, EC07, EC10, EC12, EC14, EC16, EC18 and EC10are numbered 1 to 8. Distance values are displayed on the Y axis. The top and bottom blue guidelines represent the 0.025 and 0.975 quartiles, whilethe red guideline represents the mean distance value.doi:10.1371/journal.pone.0044479.g005
Sperm DNA Methylation Profiling
PLOS ONE | www.plosone.org 9 October 2012 | Volume 7 | Issue 10 | e44479
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Sperm DNA Methylation Profiling
PLOS ONE | www.plosone.org 10 October 2012 | Volume 7 | Issue 10 | e44479
that information about what we can consider as a normal sperm
DNA methylome and whether this methylome is stable among
different normozoospermic individuals is still missing. We addressed
the above questions by using the 450 K platform which allowed us to
provide the most extensive and comprehensive investigation on
DNA methylation profile, available to date, on quality fractioned
sperm populations in a group of normozoospermic subjects. By
comparing data from the whole sperm DNA methylome [15] with
that obtained with our array, we found a highly significant
correlation Rho = 0.97 (Figure S1), indicating that our data and
conclusions are highly reliable.
Our first aim was to provide data on sperm DNA methylation
profile in quality-fractioned spermatozoa from the same subjects.
Human semen is peculiar for the heterogeneity of its sperm
population presenting a number of different qualitative features
that include kinetic, morphological, metabolic and genetic/
chromatin differences. It is for this reason that sperm selection
methods have been developed for assisted reproductive techniques
in order to obtain a highly enriched subpopulation of spermatozoa
exhibiting the best structural and functional characteristics,
indicative of optimal fertilizing ability. The question whether
these quality differences between sperm subpopulations are also
reflecting modifications in the DNA methylation pattern has not
been addressed so far. In fact, all studies published to date, except
for one, focused on either whole semen or just one selected sperm
subpopulation. Our analysis of 487,517 CpGs revealed a profound
stability of the sperm DNA methylome without significant
differences between sperm fractions enriched in ‘‘poor’’ (swim-
down) and ‘‘good’’ quality (swim-up) spermatozoa. For all
comparisons we obtained surprisingly high correlations (R2
.0.989) and the two subpopulations did not show distinct
clustering of their methylation profiles. However, by analysing
the epigenetic distances between the two sperm fractions we were
able to detect a significant difference only in one subject, although
the correlation between his two sperm subpopulations was high
also in this case, R2 = 0.9896. We separately analyzed a series of
genes for which DNA methylation defects had been previously
reported in association with impaired sperm production/quality
that included 45 imprinted genes, available on the array, and 10
additional genes selected from the literature. Despite expectation,
the DNA methylation profile of these genes showed no differences
in relationship with sperm quality. These data indicate that in
normozoospermic men, the global DNA methylation profile is not
affected significantly by structural and functional differences
between sperm subpopulations. The extensive conservation of
the DNA methylation status is especially surprising if we consider
Figure 6. Sperm DNA methylation profile (swim-up sperm samples) according to i)functional genomic distribution; ii) CpG content/neighbourhood context and iii) associated RNA transcripts. (A) Distribution of hypomethylated (n = 220.300) and hypermethylated(n = 161.542) CpGs conserved within individuals B) Distribution of variable CpGs within individuals (n = 1674).doi:10.1371/journal.pone.0044479.g006
Sperm DNA Methylation Profiling
PLOS ONE | www.plosone.org 11 October 2012 | Volume 7 | Issue 10 | e44479
that differences have been described also at the metabolic level of
‘‘poor’’ quality spermatozoa which could theoretically influence
the DNA methylation process [7,8].
The definition of sperm DNA methylation profile between
different normozoospermic subjects derives from a previous
observation showing a significant epigenetic variability in human
germ cells. Our aim was to further explore this observation both
by increasing the number of analyzed CpGs (the previous study
analyzed only12,198 CpG sites) and by comparing different sperm
fractions from different normozoospermic individuals. Our data,
clearly proved that the methylation pattern in different individuals
showing similar sperm characteristics without contaminating cells
is highly conserved. In fact, the discrepancy with the previous
study may well be due to a technical issue i.e. to the presence of
contaminating somatic cells, which could account for the observed
inter-individual differences in the methylation profile. The highest
correlation was found in the selected fraction enriched with
‘‘good’’ quality spermatozoa with R2 .0.98. This observation
indicates that regardless of slight differences in life style factors, age
and BMI, those cells which are designated to the fertilization
process (good quality sperm-enriched fraction) show a highly stable
sperm methylation profile between individuals. The few moderate
smokers (, 10 cigarettes/day) included in the study did not cluster
together, however it remains an important question whether
sperm methylome can be altered by heavy smoking or other
exogenous factors.
For the general description and comparative analyses of the
sperm DNA methylome, we focused on the fraction enriched with
‘‘good’’ quality spermatozoa showing a complete lack of significant
inter-individual differences. An interesting feature of the ‘‘normal’’
sperm DNA methylome is its highly polarized methylation profile
towards the two extreme of DNA methylation levels: hypomethy-
lation (,20%) and hypermethylation (.80%). We found that 96%
of all CpGs belonged to one of the above categories. Hypo- and
hypermethylated loci were highly conserved in different individ-
uals reaching to a concordance of 95% for hypomethylated CpGs
Figure 7. Sperm DNA methylation profile in histone-enriched regions according to i) functional genomic distribution; ii) CpGcontent/neighbourhood context; iii) associated RNA transcription. (A) Distribution of hypomethylated (n = 347) CpGs in swim-up spermsamples. (B) Distribution of hypermethylated (n = 30244) CpGs in swim-up sperm samples.doi:10.1371/journal.pone.0044479.g007
Sperm DNA Methylation Profiling
PLOS ONE | www.plosone.org 12 October 2012 | Volume 7 | Issue 10 | e44479
and to 83.3% for the hypermethylated ones. These, so called
‘‘conserved CpGs’’ were further analyzed in comparison with the
relatively few ‘‘variable CpGs’’ (0.3%) present in spermatozoa and
with the B cell DNA methylation profile. The qualitative analysis
of hypo-, hyper- and variably methylated regions showed
significant differences between the conserved hypomethylated loci
and the other two methylation categories; in fact, we observed a
significant enrichment with promoters (63.6%) and islands/shores
-linked CpGs in the hypomethylated loci. On the other hand,
among the hypermethylated and ‘‘variable’’ CpGs there was a
significant overrepresentation of gene body-linked CpGs which,
together with intergenic CpGs, build up .60% of all CpGs. The
high inter-individual conservation of hypomethylated loci, espe-
cially abundant in promoter regions, suggests that normal
spermatogenesis requires strictly controlled methylation levels in
specific gene promoters. At this regard, for the first time we
provide evidence about an exceptionally high number of
‘‘conserved’’ hypomethylated X and Y chromosome-linked loci
which further supports previous predictions on the importance of
sex chromosome linked genes in spermatogenesis and stimulates
further research on the sex chromosome methylation status in
pathological conditions [36] On the other hand, ‘‘variable’’ loci
mainly in gene bodies and intergenic sequences may indicate their
irrelevant role in spermatogenesis or may represent epigenetic
changes which may act as fine-tuners of spermatogenetic efficiency
and thus may contribute to the inter-individual variability of sperm
production in normal healthy men.
An increasing number of studies are converging on the
importance of histone-retained regions in spermatozoa for embryo
development. The first study by Hammoud et al. [14] posited that
genes involved in early embryonic development had a distinct
chromatin status in sperm, being hypomethylated, histone-
retained, enriched in H3K4me3 marks, and thus poised for
expression. On the other hand, Brykczynska et al demonstrated
that histone-retained regions with H3K27me3 mark may also play
a role in post-fertilization, whereas histone H3Lys4 demethylation
(H3K4m2) marks genes which are relevant in spermatogenesis
[37]. In addition, an other recent study reports a striking link
between the retention of nucleosomes in sperm and the
establishment of DNA methylation-free regions in the early
embryo [34]. By using the 450 K array, we found that
‘‘conserved’’ hypomethylated CpGs mapping inside histone-
enriched regions were associated with genes involved in develop-
mental processes. Accordingly, the majority of developmental gene
promoters available in the array were mapping inside histone-
retained regions. Interestingly, the correlation with developmental
genes was missing when the entire set of ‘‘conserved’’ hypomethy-
lated regions were analyzed. In fact, genes belonging to this
category are, indeed, involved in metabolic processes which
indicate a differential biological function of genes situated in
histone-enriched and histone-depleted regions.
The most relevant finding concerning the comparison between
the DNA methylation profiles of the male germ cell and the B cell, is
that only a minority of CpGs showed differential methylation (4.6%)
between the two cell types and was mainly due to the overrepre-
sentation of hypomethylated loci in spermatozoa. A total of 3,344
distinct genes were related to sperm-specific hypomethylated CpGs
and among the strongest associations appeared ‘‘DNA methylation
involved in gamete generation’’ and ‘‘piRNA metabolic processes’’.
Similarly to the general sperm DNA methylome data, those genes
(n = 195) which were hypomethylated in histone-retained regions
were involved in developmental processes (organogenesis, especially
neuronal development) and spermatogenesis. The different meth-
ylation, in respect to the somatic cell, of the promoters of
spermatogenesis genes is in accordance with the well known
importance of epigenetic regulation of cell specific functions. The
association with developmental genes further reinforces the
hypothesis about a programmed histone retention in spermatozoa,
which would serve for rapid activation of genes involved in
embryonic development.
Finally, the complete lack of studies focusing on the methylation
status of piRNAs in spermatozoa prompted us to provide a detailed
analysis of this specific class of small non coding RNAs. Although
piRNAs were first described as specifically expressed in the testis,
Figure 8. Bar graph illustrating the percentage of hypermethylated and hypomethylated CpGs in swim-up sperm samples and Bcells. The number of detected CpGs varies according to the data extrapolation performed separately for each tested group: i) total CpGs, ii)autosomal CpGs, iii) X chromosome-linked CpGs and iv) Y chromosome-linked CpGs. * corresponds to p values ,0.05 (the whiskers show the SD;n = 7).doi:10.1371/journal.pone.0044479.g008
Sperm DNA Methylation Profiling
PLOS ONE | www.plosone.org 13 October 2012 | Volume 7 | Issue 10 | e44479
recent data suggest their potential role in tumorigenesis and in
somatic cell function [29,30]. In addition the presence of
piRNAs has been also described in spermatozoa [38]. The 450K
array is able to provide the characterization of a total of 2,591
unique piRNAs covered by 7,528 CpGs on the array. In
spermatozoa we found a significantly higher proportion of
piRNA-linked CpGs within the total hypomethylated loci
compared to those found within the hypermethylated loci
(p = 1.585E-05). The preferential hypomethylation of piRNAs
was evident also in comparison with two other cell types: a
differentiated somatic cell type (B cell) and a colon cancer cell
type (HCT116). In fact, in spermatozoa 48.6% of CpGs were
Figure 9. Spermatozoa versus B cell: a 450K DNA methylation portrait. (A) Graph showing percentages of equally and differentiallymethylated CpG sites in swim-up sperm samples compared to B cells. (B) Graph showing percentages of hypermethylation and hypomethylation inspermatozoa relating to the differentially methylated CpGs proportion (4,3%). Graphs describing the hypermethylated (C) and hypomethylated (D)sites according to their i) functional genomic distribution; ii) CpG content/neighborhood context and iii) association with RNA transcripts.doi:10.1371/journal.pone.0044479.g009
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hypomethylated, whereas the percentages were 26% and 4.5%
in HCT116 and B cell, respectively. Intriguingly, among those
piRNAs which were located in histone-retained regions in
spermatozoa, 97% of them showed low level of methylation.
This observation represents a starting point for future studies
aimed to explore the biological significance of these cell-
dependent differences. An additional novel finding concerns the
involvement of piRNA-related genes in distinct biological
processes according to the methylation status of the related
piRNAs. Most importantly, hypomethylated piRNAs are linked
to genes associated with embryonic development and cell
adhesion. Interestingly, piRNAs in histone-retained regions,
showing hypomethylation exclusively in spermatozoa, are
involved in the negative regulation of metabolic and biosyn-
thetic processes which could be potentially relevant to the
embryo. Given that almost all of these piRNAs are located
inside or in the 39UTR regions of the abovementioned genes, a
potential RNA interfering mechanism can be hypothesized
[29,39]. The interference with those RNAs which would have a
negative regulatory effect on metabolism and biosynthesis may
have an important biological function in early embryonic
development.
In conclusion, our study, based on the largest number of
subjects ever considered for such a high number of CpGs,
provided clear evidence of a highly conserved DNA methylation
profile among normozoospermic subjects. We also demonstrated
that sperm methylation is stable in different quality-fractioned
sperm subpopulations of the same individual i.e. sperm methyl-
ation is not altered in ‘‘poor’’ quality spermatozoa of normozoo-
spermic men despite the fact that these cells are clearly different
from a metabolic and DNA integrity point of view. In addition,
our array-based analysis provided both confirmatory and novel
data concerning the ‘‘normal’’ sperm DNA methylome, including
its peculiar features in respect to somatic and cancer cells. Our
description about a highly polarized sperm methylation profile,
the clearly distinct genomic and functional organization of hypo
versus hypermethylated loci and the association of histone-
enriched hypomethylated loci with embryonic development,
which we now extended also to hypomethylated piRNAs-linked
genes, represents a solid basis for future basic and clinically
oriented research.
Supporting Information
Figure S1 Comparison of the methylation levels ob-tained in the array versus data reported in Molaro et alpaper (ref 15). Heatmap generated from the distance correla-
tion matrix for the 8 individual samples ‘‘up’’ (A) and ‘‘down’’ (B),
the scale of the correlation is shown above the matrix (scale values
from 0 to 0.03); Correlation scatter plots between Molaros data vs
the average methylation level for all ‘‘up’’ samples (C) and ‘‘down’’
samples (D), the Pearson correlation coefficient (rho) is shown.
(DOC)
Table S1 Clinical description of the 8 normozoospermicindividuals.
(DOC)
Figure 10. Venn diagram reporting unique and overlapping CpGs in/between the three cell types. A) Hypermethylated CpGs. B)Hypomethylated CpGs. C) Hypomethylated CpGs in histone-retained regions. HCT116: colorectal cancer cell line.doi:10.1371/journal.pone.0044479.g010
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PLOS ONE | www.plosone.org 15 October 2012 | Volume 7 | Issue 10 | e44479
Table S2 Analysis of intra-and inter-individual variabil-ity of the sperm DNA methylation profile: estimate ofcorrelation coefficients.
(DOC)
Table S3 Analysis of inter-individual variability of thesperm DNA methylation profile: epigenetic distance andcoefficient of variation.
(DOC)
Table S4 Biological processes associated with geneslinked to ‘‘conserved’’ hypo- and hypermethylated CpGloci in spermatozoa.
(DOC)
Table S5 Biological processes associated with geneslinked to sperm-specific hypomethylated CpG loci.
(DOC)
Table S6 Biological processes associated with geneslinked to piRNAs specifically hypo or hypermethylatedin spermatozoa.(DOC)
Acknowledgments
We thank Paolo Sassone-Corsi (University of California, Irvine, USA), Jose
Sanchez-Mut and Javier Carmona-Sanz (Idibell, Barcelona, Catalonia,
Spain) for helpful discussions of the results. We thank Sue Hammoud and
Doug Carrell (University of Utah, Salt lake City, USA) for providing us
with their data regarding the histone-enriched loci. Sebastian Moran
Salama y Carles Arribas Jorba (Idibell, Barcelona, Catalonia, Spain) are
aknowledged for their technical assistance.
Author Contributions
Conceived and designed the experiments: CK ME. Performed the
experiments: JS CC CG. Analyzed the data: CK JS SS. Contributed
reagents/materials/analysis tools: CK ME HH. Wrote the paper: CK JS.
References
1. Matzuk MM, Lamb DJ (2008) The biology of infertility: research advances andclinical challenges. Nat Med 14: 1197–1213.
2. World Health Organization (2010) WHO laboratory manual for theExamination and processing of human semen. Fifth Edition: WHO Press.
3. Eckardstein SV, Schmidt A, Kamischke A, Simoni M, Gromoll J, et al. (2002)
CAG repeat length in the androgen receptor gene and gonadotrophinsuppression influence the effectiveness of hormonal male contraception. Clin
Endocrinol (Oxf) 57: 647–655.4. Giachini C, Laface I, Guarducci E, Balercia G, Forti G, et al. (2008) Partial
AZFc deletions and duplications: clinical correlates in the Italian population.
Hum Genet 124: 399–410.5. Giachini C, Nuti F, Turner DJ, Laface I, Xue Y, et al. (2009) TSPY1 copy
number variation influences spermatogenesis and shows differences among Ylineages. J Clin Endocrinol Metab 94: 4016–4022.
6. Guarducci E, Nuti F, Becherini L, Rotondi M, Balercia G, et al. (2006) Estrogenreceptor alpha promoter polymorphism: stronger estrogen action is coupled with
lower sperm count. Hum Reprod 21: 994–1001.
7. Huszar G, Vigue L, Corrales M (1988) Sperm creatine phosphokinase activity asa measure of sperm quality in normospermic, variablespermic, and oligospermic
men. Biol Reprod 38: 1061–1066.8. Orlando C, Krausz C, Forti G, Casano R (1994) Simultaneous measurement of
sperm LDH, LDH-X, CPK activities and ATP content in normospermic and
oligozoospermic men. Int J Androl 17: 13–18.9. Gandini L, Lombardo F, Paoli D, Caruso F, Eleuteri P, et al. (2004) Full-term
pregnancies achieved with ICSI despite high levels of sperm chromatin damage.Hum Reprod 19: 1409–1417.
10. Jackson RE, Bormann CL, Hassun PA, Rocha AM, Motta EL, et al. (2010)Effects of semen storage and separation techniques on sperm DNA
fragmentation. Fertil Steril 94: 2626–2630.
11. Marchesi DE, Biederman H, Ferrara S, Hershlag A, Feng HL (2010) The effectof semen processing on sperm DNA integrity: comparison of two techniques
using the novel Toluidine Blue Assay. Eur J Obstet Gynecol Reprod Biol 151:176–180.
12. Spano M, Cordelli E, Leter G, Lombardo F, Lenzi A, et al. (1999) Nuclear
chromatin variations in human spermatozoa undergoing swim-up andcryopreservation evaluated by the flow cytometric sperm chromatin structure
assay. Mol Hum Reprod 5: 29–37.13. Flanagan JM, Popendikyte V, Pozdniakovaite N, Sobolev M, Assadzadeh A, et
al. (2006) Intra- and interindividual epigenetic variation in human germ cells.Am J Hum Genet 79: 67–84.
14. Hammoud SS, Nix DA, Zhang H, Purwar J, Carrell DT, et al. (2009) Distinctive
chromatin in human sperm packages genes for embryo development. Nature460: 473–478.
15. Molaro A, Hodges E, Fang F, Song Q, McCombie WR, et al. (2011) Spermmethylation profiles reveal features of epigenetic inheritance and evolution in
primates. Cell 146: 1029–1041.
16. Navarro-Costa P, Nogueira P, Carvalho M, Leal F, Cordeiro I, et al. (2010)Incorrect DNA methylation of the DAZL promoter CpG island associates with
defective human sperm. Hum Reprod 25: 2647–2654.17. Boissonnas CC, Abdalaoui HE, Haelewyn V, Fauque P, Dupont JM, et al.
(2010) Specific epigenetic alterations of IGF2-H19 locus in spermatozoa from
infertile men. Eur J Hum Genet 18: 73–80.18. Hammoud SS, Nix DA, Hammoud AO, Gibson M, Cairns BR, et al. (2011)
Genome-wide analysis identifies changes in histone retention and epigeneticmodifications at developmental and imprinted gene loci in the sperm of infertile
men. Hum Reprod 26: 2558–2569.
19. Hammoud SS, Purwar J, Pflueger C, Cairns BR, Carrell DT (2009) Alterationsin sperm DNA methylation patterns at imprinted loci in two classes of infertility.
Fertil Steril 94: 1728–1733.20. Houshdaran S, Cortessis VK, Siegmund K, Yang A, Laird PW, et al. (2007)
Widespread epigenetic abnormalities suggest a broad DNA methylation erasure
defect in abnormal human sperm. PLoS One 2: e1289.21. Kobayashi H, Sato A, Otsu E, Hiura H, Tomatsu C, et al. (2007) Aberrant DNA
methylation of imprinted loci in sperm from oligospermic patients. Hum MolGenet 16: 2542–2551.
22. Marques CJ, Costa P, Vaz B, Carvalho F, Fernandes S, et al. (2008) Abnormal
methylation of imprinted genes in human sperm is associated with oligozoos-permia. Mol Hum Reprod 14: 67–74.
23. Marques CJ, Francisco T, Sousa S, Carvalho F, Barros A, et al. (2010)Methylation defects of imprinted genes in human testicular spermatozoa. Fertil
Steril 94: 585–594.24. Pacheco SE, Houseman EA, Christensen BC, Marsit CJ, Kelsey KT, et al.
(2011) Integrative DNA methylation and gene expression analyses identify DNA
packaging and epigenetic regulatory genes associated with low motility sperm.PLoS One 6: e20280.
25. Poplinski A, Tuttelmann F, Kanber D, Horsthemke B, Gromoll J (2010)Idiopathic male infertility is strongly associated with aberrant methylation of
MEST and IGF2/H19 ICR1. Int J Androl 33: 642–649.
26. Aravin AA, Hannon GJ (2008) Small RNA silencing pathways in germ and stemcells. Cold Spring Harb Symp Quant Biol 73: 283–290.
27. Deng W, Lin H (2002) miwi, a murine homolog of piwi, encodes a cytoplasmicprotein essential for spermatogenesis. Dev Cell 2: 819–830.
28. Kuramochi-Miyagawa S, Kimura T, Ijiri TW, Isobe T, Asada N, et al. (2004)Mili, a mammalian member of piwi family gene, is essential for spermatogenesis.
Development 131: 839–849.
29. Juliano C, Wang J, Lin H (2011) Uniting Germline and Stem Cells: TheFunction of Piwi Proteins and the piRNA Pathway in Diverse Organisms. Annu
Rev Genet 45: 447–469.30. Siddiqi S, Matushansky I (2011) Piwis and piwi-interacting RNAs in the
epigenetics of cancer. J Cell Biochem.
31. Sandoval J, Heyn H, Moran S, Serra-Musach J, Pujana MA, et al. Validation ofa DNA methylation microarray for 450,000 CpG sites in the human genome.
Epigenetics 6: 692–702.32. Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, et al. (2011) High density DNA
methylation array with single CpG site resolution. Genomics 98: 288–295.33. Falcon S, Gentleman R (2007) Using GOstats to test gene lists for GO term
association. Bioinformatics 23: 257–258.
34. Vavouri T, Lehner B Chromatin organization in sperm may be the majorfunctional consequence of base composition variation in the human genome.
PLoS Genet 7: e1002036.35. Carrell DT, Hammoud SS (2010) The human sperm epigenome and its
potential role in embryonic development. Mol Hum Reprod 16: 37–47.
36. Marques CJ, Carvalho F, Sousa M, Barros A (2004) Genomic imprinting indisruptive spermatogenesis. Lancet 363: 1700–1702.
37. Brykczynska U, Hisano M, Erkek S, Ramos L, Oakeley EJ, et al. (2010)Repressive and active histone methylation mark distinct promoters in human
and mouse spermatozoa. Nat Struct Mol Biol 17: 679–687.
38. Krawetz SA, Kruger A, Lalancette C, Tagett R, Anton E, et al. (2011) A surveyof small RNAs in human sperm. Hum Reprod 26: 3401–3412.
39. Esposito T, Magliocca S, Formicola D, Gianfrancesco F (2011) piR_015520belongs to Piwi-associated RNAs regulates expression of the human melatonin
receptor 1A gene. PLoS One 6: e22727.
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PLOS ONE | www.plosone.org 16 October 2012 | Volume 7 | Issue 10 | e44479
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